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arXiv · 2001.01400

Model Predictive Control for Finite Input Systems using the D-Wave Quantum Annealer

Daisuke Inoue·Hiroaki Yoshida
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Abstract

The D-Wave quantum annealer has emerged as a novel computational architecture that is attracting significant interest, but there have been only a few practical algorithms exploiting the power of quantum annealers. Here we present a model predictive control (MPC) algorithm using a quantum annealer for a system allowing a finite number of input values. Such an MPC problem is classified as a non-deterministic polynomial-time-hard combinatorial problem, and thus real-time sequential optimization is difficult to obtain with conventional computational systems. We circumvent this difficulty by converting the original MPC problem into a quadratic unconstrained binary optimization problem, which is then solved by the D-Wave quantum annealer. Two practical applications, namely stabilization of a spring-mass-damper system and dynamic audio quantization, are demonstrated. For both, the D-Wave method exhibits better performance than the classical simulated annealing method. Our results suggest new applications of quantum annealers in the direction of dynamic control problems.

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Daisuke Inoue, Hiroaki Yoshida. 2020-01-06. Model Predictive Control for Finite Input Systems using the D-Wave Quantum Annealer. https://doi.org/10.1038/s41598-020-58081-9

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